PSYCHOPHYSICAL EXPERIMENTS

A LETTER MATCHING TASKPOSNER

MENTAL REPRESENTATION

A letter-matching task

(Posner) – Chronometric

(reaction time task)

Reaction time (RT) of

subject is the dependent

variable.

Response time can show

how fast each

representation is activated

q) Why ‘both consonants’

condition takes longer for

response than ‘both vowels’

condition?

MEMORY COMPARISON TASK(MEMORY-SCANNING TASK)

SAUL STERNBERG

REPRESENTATIONS ARE TRANSFORMED

Saul Sternberg (1975) Memory comparison task

Exhausting vs. self-terminating search

WORD SUPERIORITY EFFECTREICHER

TWO ALTERNATIVE FORCED CHOICE PARADIGM

PARALLEL VS. SERIAL PROCESSES

Reicher (1969) Word superiority effect

Two alternative forced choice

Does the stimulus contain an A or E?

(press A or E)

SPATIAL ATTENTION TASKPOSNER CUING TASK

POSNER CUING TASK

FEATURE SEARCH VS.

CONJUNCTION SEARCHTREISMAN

FEATURE VS. CONJUNCTION SEARCH

STROOP TASKMULTIPLICITY OF MENTAL REPRESENTATIONS

MULTIPLICITY OF MENTAL REPRESENTATIONS

빨강

초록

파랑

노랑

검정

MULTIPLICITY OF MENTAL REPRESENTATIONS

빨강

초록

파랑

노랑

검정

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MULTIPLICITY OF MENTAL REPRESENTATIONS

빨강

초록

파랑

노랑

검정

노랑

파랑

빨강

검정

초록

XXXX

XXXX

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MODULES AND FUNCTIONS

clear all

clc

% Set constants

applications = 30;

max_admits_allowed = 10;

IQmean = 110;

IQsd = 20;

SATQmean = 500;

SATQsd = 100;

SATVmean = 500;

SATVsd = 100;

ECsd = 10;

GPAmean = 2.0;

GPAsd = 10;

SCRIPT

% Preallocate arrays using deal

[IQ SATQ SATV GPA Acad EC Dist] =

deal(zeros(applications,1));

% Generate dummy scores to test the program

IQ = IQmean + (randn(applications,1)) * IQsd;

SATQ = SATQmean + (randn(applications,1)) * SATQsd;

SATV = SATVmean + (randn(applications,1)) * SATVsd;

GPA = GPAmean + (randn(applications,1)) * GPAsd;

EC = abs(randn(applications,1) * ECsd);

Dist = abs(randn(applications,1));

Acad = SATQ + SATV + 100 * GPA;

% Normalize the scores

Acad = (Acad - min(Acad)) ./ (max(Acad)-min(Acad));

EC = (EC -min(EC)) ./(max(EC)-min(EC));

Dist = (Dist - min(Dist)) ./(max(Dist)-min(Dist));

% Create a Scores matrix, including, in the final column,

% each student's total score

Scores = [[1:applications]' Acad EC Dist];

Scores(:,5) = [Acad + EC + Dist];

SCRIPT

% Admit the top max_admits_allowed students (plus any ties)

SortedScores = sortrows(Scores,-5);

criterion = SortedScores(max_admits_allowed,5);

SortedScores(:,6) = 0;

SortedScores((SortedScores(:,5) >= criterion),6) = 1;

ScoresAndAcceptances = sortrows(SortedScores,1);

% Display the results

fprintf('App.\tAcad.\tExtra.\tDist.\tTotal\tAccept\n\n')

fprintf(...

'%4d\t%6.2f\t%6.2f\t%6.2f\t%6.2f\t%4d\n',ScoresAndAcceptances')

fprintf('\r')

Students_Accepted = find(ScoresAndAcceptances(:,6));

fprintf('Accepted Students:\n');

fprintf('%3d',Students_Accepted);

fprintf('\n\n')

fprintf('Cutoff score: %5.03f\n', criterion);

SCRIPT

%College_Admissions_Main.m

Clear_Start;

Set_Constants;

Generate_Dummy_Scores;

Normalize_Scores;

Create_Scores_Matrix;

Select_Students;

Display_Results;

DIVIDING INTO SMALL MODULES

SCRIPT VS. FUNCTION

% function mymean.m

function myresult = mymean(inputarray);

myresult = sum(inputarray)/length(inputarray)

Return

meanD = mymean([1 3 5 7 9])

meanE = mymean([pi 1492 6.02])

meanF = mymean([1:10])

meanD =

5

meanE =

500.3872

meanF =

5.5000

FUNCTION

FUNCTION

% normalize.m

function y = normalize(x)

y = (x-min(x))./(max(x)-min(x));

end

% normalize_split_two_args.m

% Splits array in first argument into

% lower and upper halves, using the

% criterion ('mean' or 'median')

% specified in the second argument

function [ly, uy] =

normalize_split_two_args(x,typeofsplit);

lx = [];

ux = [];

if strcmp(typeofsplit,'median') % median split

lx = x(x<=median(x));

ux = x(x>median(x));

elseif strcmp(typeofsplit,'mean') % mean split

lx = x(x<=mean(x));

ux = x(x>mean(x));

FUNCTION WITH MORE THAN ONE ARGUMENT

else % error feedback

disp(['Error: An invalid type of split'...

' in the call to normalize_split_two_args']);

[ly, uy] = deal(NaN);

return

end

ly = (lx - min(lx)) ./ (max(lx)- min(lx));

uy = (ux - min(ux)) ./ (max(ux)- min(ux));

return

% mean_and_trimmed_mean.m

function [y,ty] = mean_and_trimmed_mean(x)

y = mean(x);

ty = mean(trimmed(x));

return

function zz = trimmed(w)

w = sort(w);

zz = [w(2:end-1)];

return

CREATING MULTIPLE FUNCTIONS IN A FILE

% ComputeMeans_Fails.m

x = randperm(5).^2;

[theMean theTrimmedMean] = mean_and_trimmed_mean(x)

function [y,ty] = mean_and_trimmed_mean(x)

y = mean(x);

ty = mean(trimmed(x));

return

function zz = trimmed(w)

w = sort(w);

zz = [w(2:end-1)];

return

CREATING MULTIPLE FUNCTIONS IN A FILE

% ComputeMeans_Succeeds.m

function main

x = randperm(5).^2

[theMean theTrimmedMean] = mean_and_trimmed_mean(x)

return

end % main function

function [y,ty] = mean_and_trimmed_mean(x)

y = mean(x);

ty = mean(trimmed(x));

return

end % mean_and_trimmed_mean

function zz = trimmed(w)

w = sort(w);

zz = [w(2:end-1)];

return

end % trimmed

CREATING MULTIPLE FUNCTIONS IN A FILE

PLOTS

clear all

close all

figure(1)

theta_rad = linspace(0,4*(2*pi),100);

plot(theta_rad,sin(theta_rad));

CONTROLLING PLOTS

clear all

close all

figure(1)

theta_rad = linspace(0,4*(2*pi),100);

plot(theta_rad,sin(theta_rad));

axis([min(theta_rad) max(theta_rad)

min(sin(theta_rad)) max(sin(theta_rad))]);

CONTROLLING PLOTS

clear all

close all

figure(1)

theta_rad = linspace(0,4*(2*pi),100);

x = theta_rad;

y = sin(theta_rad);

plot(x,y);

x_offset = 1;

y_offset = 0.2;

xlim([min(x)-x_offset, max(x+x_offset)]);

ylim([min(y)-y_offset, max(y+y_offset)]);

CONTROLLING PLOTS

clear all

close all

figure(1)

theta_rad = linspace(0,4*(2*pi),100);

x = theta_rad;

y = sin(theta_rad);

plot(x,y, 'g-');

hold on

plot(x,y, 'bo');

x_offset = 1;

y_offset = 0.2;

xlim([min(x)-x_offset, max(x+x_offset)]);

ylim([min(y)-y_offset, max(y+y_offset)]);

CONTROLLING PLOTS

clear all

close all

figure(1)

theta_rad = 0:.1:2*pi;

x = theta_rad;

y = sin(theta_rad);

plot(x,y,'go-');

hold on

y = cos(theta_rad);

plot(x,y,'b-s');

x_offset = 1;

y_offset = 0.2;

xlim([min(x)-x_offset, max(x+x_offset)]);

ylim([min(y)-y_offset, max(y+y_offset)]);

shg

CONTROLLING PLOTS

figure(1)

theta_rad = 0:.1:2*pi;

x = theta_rad;

plot(x,sin(theta_rad),'c+:', x, cos(theta_rad),

'rd');

CONTROLLING PLOTS

clear all

close all

figure(1)

theta_rad = 0:.1:8*pi;

x = theta_rad;

y = sin(x);

plot(x,y,'g-');

hold on

x_offset = 0;

y_offset = .2;

axis([min(x)-x_offset, max(x)+x_offset, ...

min(y)-y_offset, max(y+y_offset)]);

plot(x,y,'o','color','r','markersize',6,...

'markeredgecolor','k','markerfacecolor','r');

xlabel('Time');

ylabel('Happiness');

title('Life has its ups and downs');

CONTROLLING PLOTS